In today's increasingly competitive manufacturing industry, automated production lines have long
been no novelty. However, invested heavily in the introduction of advanced equipment, whether the
real transformation to match the productivity? In reality, many automated production lines are still
mired in the efficiency quagmire: expensive machines are idle from time to time, the production beat
is sometimes fast and sometimes slow, time-consuming change of line lengthy, abnormal handling
of the hands and feet... The efficient operation of automation equipment, far from simply pressing
the start button can be achieved, it is a sophisticated synergy and continuous optimization of the
depth of the battle.
Efficiency dilemma: the invisible loss of automated production lines
Equipment “on duty with disease”: Neglect of preventive maintenance, equipment failure is frequent,
the production line is forced to interrupt. Once the key equipment “strike”, the entire production line is
paralyzed, the recovery time is long, huge loss of production capacity. “Equipment lying down for an
hour, the whole day's output soaked half” has become the true picture of many workshops.
Bottleneck link neck: The capacity of the production line is uneven, the slowest link (bottleneck station)
determines the overall output speed. Bottleneck station before the pile of materials, the subsequent
station but “no rice to cook”, equipment idling or inefficient operation. Failure to accurately identify and
overcome bottlenecks, automation advantages will be ruthlessly diluted.
Mold change line “marathon”: product switching, mold replacement, parameter adjustment, the first piece
of confirmation and other links take too long. Frequent line change leads to a significant reduction in
effective production time, “two hours to change the line, the production of a quarter of an hour,” the
dilemma is not uncommon.
Data sleep, decision-making by “guessing”: line equipment generates a huge amount of operational data
(speed, status, energy consumption, fault code), but has not been effectively collected, integrated and
analyzed. Managers lack a clear understanding of the real efficiency of equipment (OEE), causes of downtime,
production bottlenecks, vague direction of improvement, decision-making is like a blind man feeling an elephant.
Slow response to abnormalities: When there are abnormalities in production (e.g., quality fluctuations,
material shortages, equipment malfunctions), the chain of information transfer is long and the response is
slow. Operators need to leave their positions to find support, further lengthening downtime.
Efficiency Breakthrough: The Core Strategy for Activating
Automated Production Lines
Efficiency from the equipment: Strengthening the foundation of reliable operation
Implement Predictive Maintenance (PdM): Go beyond traditional scheduled maintenance. Deploy sensors
(e.g., vibration, temperature, current) on critical equipment to monitor its “state of health” in real time. By
combining historical data with operational models, we can predict potential failure points and precisely schedule
maintenance windows to nip failures in the bud and maximize equipment availability.
Standardized Maintenance Operations (SOPs): Develop clear, illustrated operating procedures (SOPs) for daily
inspection, regular maintenance, and troubleshooting of each type of equipment. Ensure that maintenance actions
are standardized and efficient, and reduce additional downtime due to improper operation or process confusion.
Lean Management of Critical Spare Parts: Identify high wear and tear, long-cycle spare parts for critical equipment
and establish safety stock. Optimize spare parts storage locations to ensure quick access. Apply barcode/RFID
technology to manage spare parts inventory to avoid long waiting time due to missing parts.
Capacity from bottlenecks: Opening up “choke points” in the production flow.
Technology upgrade: Evaluate the feasibility of automating bottleneck stations, adding parallel stations or
introducing more efficient equipment.
Process Optimization: Simplify the steps at the bottleneck station, optimize the parameters of the machining program,
and reduce ineffective movements or waiting time.
Resource Prioritization: Ensure bottleneck stations have priority access to materials, maintenance support and skilled operators.
Accurate identification of bottlenecks: Use value stream mapping (VSM) and other methods to record the actual
processing time and waiting time at each station. Continuously monitor the capacity of each station to identify the
real bottlenecks that are constraining overall output (typically the stations with the longest processing times or the
highest failure rates).
Concentrate your efforts on the bottleneck:
Balance the production line beat: After the bottleneck capacity is increased, re-evaluate and adjust the resource allocation
of other stations (e.g., personnel, equipment speed), so that the capacity of each link of the entire production line is matched
as evenly as possible, and a smooth single-piece flow is realized.
Ask for time to changeover: Realize fast and flexible production changeover.
Distinguish between internal and external operations: Strictly differentiate mold changeover operations into “internal
operations” that must be carried out when the equipment is shut down and “external operations” that can be prepared
when the equipment is running (e.g., preheating molds, preparing tools, and putting materials in place).
Internal to external: Maximize the conversion of “internal jobs” into “external jobs”.
Optimization of internal operations: Simplification of operational steps, use of standardized fasteners (e.g. hydraulic
clamps, locating pins), modular design, reduction of adjustment and commissioning times. Use of visual instructions.
Intensive practice of SMED (quick mold change):
Implement standardized operations: Develop detailed and optimized standard operating procedures (SOPs) for each
product changeover, and provide sufficient training and drills to operators to ensure that each changeover is precise,
efficient, and consistent.
Ask for insights from data: drive accurate decision-making and optimization.
Bottleneck Location: Through OEE hierarchical drilling, precisely analyze the loss of each workstation and target efficiency pockets.
Root Cause Analysis: In-depth analysis of major downtime types (e.g., malfunction, mold change, pending material) to
identify root causes and guide targeted improvements.
Forecasting: Based on historical data modeling, predict potential equipment failures, maintenance needs, or capacity
bottleneck risks and intervene in advance.
Continuous Improvement Closed Loop: Based on data insights, formulate improvement measures and track the effect
of improvement, forming a PDCA cycle.
Build production line IOT network: Install data collection interfaces (e.g. PLC communication, sensors) for equipment to
realize real-time and automatic collection of data on equipment operation status (start/stop, speed, mode), process
parameters, fault alarms and so on.
Establishment of a unified monitoring platform: Integrate data from equipment, MES (Manufacturing Execution System),
and safety and light systems to build a centralized monitoring platform (SCADA/HMI) at the production line or factory level.
Real-time visualization of key indicators: OEE (availability x performance x yield), plan achievement rate, real-time production,
downtime and cause distribution, etc.
Deepen data analysis and application:
Demand speed from anomalies: build an agile response mechanism
Deploy Andon system: Set up pull cords or buttons at workstations, which are instantly triggered when operators find
abnormalities (quality, material, equipment, safety). The system quickly transmits abnormal information through sound and
light alarms, Kanban displays, and information push (to team leaders, maintenance, materials, etc.).
Establish a hierarchical response process: Define the standard response personnel, timeframe and escalation path for
different levels of exceptions. Ensure that problems are handled at the appropriate level in the shortest possible time
to avoid delays.
Implement rapid on-site response: Require support staff (maintenance, quality, logistics) to be on standby in a
fixed area or quickly arrive at the scene. Equipped with mobile terminals to receive real-time information on safety
lights to improve response speed.
Efficiency Improvement: The Never-Ending Lean Journey
Efficiency improvement of automated production lines is never an overnight engineering transformation, but a continuous
refinement integrated into daily life. It requires managers to look beyond the speed of a single piece of equipment to a
broader dimension: the reliable breathing rhythm of the equipment, the smooth running pulse of the production line, the
precise insights of the data, and the agile responsiveness of the team.
When the sensor becomes the “stethoscope” of the equipment, and the data platform becomes the “intelligent brain”
of the production line, every production change is like flowing water, and every abnormality can be instantly captured and
resolved, so the automated production line can really get rid of the boundaries of the tangible and intangible, and unleash
its The ultimate battlefield of efficiency lies in the elimination of
The ultimate battlefield of efficiency lies in eliminating all forms of waste and stagnation. Let every piece of equipment,
every minute, every material, are in the value of the track running at full speed. This is not only the triumph of technology,
but also the concentrated manifestation of manufacturing wisdom and management toughness, driving enterprises to
break the waves in the wave of efficiency and win the future.